Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations2969
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory301.5 KiB
Average record size in memory104.0 B

Variable types

Numeric12

Alerts

avg_basket_size is highly overall correlated with gross_revenue and 1 other fieldsHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_unique_basket_sizeHigh correlation
avg_unique_basket_size is highly overall correlated with avg_ticket and 1 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qtd_invoices is highly overall correlated with gross_revenue and 3 other fieldsHigh correlation
qtd_items is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qtd_products is highly overall correlated with avg_unique_basket_size and 3 other fieldsHigh correlation
recency_days is highly overall correlated with qtd_invoicesHigh correlation
avg_ticket is highly skewed (γ1 = 53.44422359) Skewed
frequency is highly skewed (γ1 = 24.88049136) Skewed
qtd_returns is highly skewed (γ1 = 51.79774426) Skewed
avg_basket_size is highly skewed (γ1 = 44.67271661) Skewed
customer_id has unique values Unique
recency_days has 34 (1.1%) zeros Zeros
qtd_returns has 1481 (49.9%) zeros Zeros

Reproduction

Analysis started2025-03-09 13:10:12.553973
Analysis finished2025-03-09 13:10:42.168387
Duration29.61 seconds
Software versionydata-profiling vv4.13.0
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Unique 

Distinct2969
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15270.773
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-09T10:10:42.353467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12619.4
Q113799
median15221
Q316768
95-th percentile17964.6
Maximum18287
Range5940
Interquartile range (IQR)2969

Descriptive statistics

Standard deviation1718.9903
Coefficient of variation (CV)0.11256734
Kurtosis-1.2060947
Mean15270.773
Median Absolute Deviation (MAD)1488
Skewness0.031607859
Sum45338925
Variance2954927.6
MonotonicityNot monotonic
2025-03-09T10:10:42.573518image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12558 1
 
< 0.1%
17850 1
 
< 0.1%
13047 1
 
< 0.1%
12583 1
 
< 0.1%
13748 1
 
< 0.1%
15100 1
 
< 0.1%
15291 1
 
< 0.1%
14688 1
 
< 0.1%
17809 1
 
< 0.1%
16956 1
 
< 0.1%
Other values (2959) 2959
99.7%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18277 1
< 0.1%
18276 1
< 0.1%
18274 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18269 1
< 0.1%

gross_revenue
Real number (ℝ)

High correlation 

Distinct2954
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2749.3217
Minimum6.2
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-09T10:10:42.777567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile229.77
Q1570.96
median1086.92
Q32308.06
95-th percentile7219.68
Maximum279138.02
Range279131.82
Interquartile range (IQR)1737.1

Descriptive statistics

Standard deviation10580.623
Coefficient of variation (CV)3.8484486
Kurtosis353.94472
Mean2749.3217
Median Absolute Deviation (MAD)672.16
Skewness16.777556
Sum8162736.2
Variance1.1194959 × 108
MonotonicityNot monotonic
2025-03-09T10:10:42.990620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
533.33 2
 
0.1%
734.94 2
 
0.1%
178.96 2
 
0.1%
1078.96 2
 
0.1%
598.2 2
 
0.1%
1314.45 2
 
0.1%
379.65 2
 
0.1%
2053.02 2
 
0.1%
331 2
 
0.1%
889.93 2
 
0.1%
Other values (2944) 2949
99.3%
ValueCountFrequency (%)
6.2 1
< 0.1%
13.3 1
< 0.1%
15 1
< 0.1%
36.56 1
< 0.1%
45 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
168472.5 1
< 0.1%
140450.72 1
< 0.1%
124564.53 1
< 0.1%
117379.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%

recency_days
Real number (ℝ)

High correlation  Zeros 

Distinct272
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.287639
Minimum0
Maximum373
Zeros34
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-09T10:10:43.208662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median31
Q381
95-th percentile242
Maximum373
Range373
Interquartile range (IQR)70

Descriptive statistics

Standard deviation77.756779
Coefficient of variation (CV)1.2095137
Kurtosis2.7779627
Mean64.287639
Median Absolute Deviation (MAD)26
Skewness1.7983795
Sum190870
Variance6046.1167
MonotonicityNot monotonic
2025-03-09T10:10:43.557722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.3%
4 87
 
2.9%
3 85
 
2.9%
2 85
 
2.9%
8 76
 
2.6%
10 67
 
2.3%
9 66
 
2.2%
7 66
 
2.2%
17 64
 
2.2%
16 55
 
1.9%
Other values (262) 2219
74.7%
ValueCountFrequency (%)
0 34
 
1.1%
1 99
3.3%
2 85
2.9%
3 85
2.9%
4 87
2.9%
5 43
1.4%
7 66
2.2%
8 76
2.6%
9 66
2.2%
10 67
2.3%
ValueCountFrequency (%)
373 2
0.1%
372 4
0.1%
371 1
 
< 0.1%
368 1
 
< 0.1%
366 4
0.1%
365 2
0.1%
364 1
 
< 0.1%
360 1
 
< 0.1%
359 1
 
< 0.1%
358 4
0.1%

qtd_invoices
Real number (ℝ)

High correlation 

Distinct56
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7231391
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-09T10:10:43.782774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile17
Maximum206
Range205
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.8565313
Coefficient of variation (CV)1.5474954
Kurtosis190.83445
Mean5.7231391
Median Absolute Deviation (MAD)2
Skewness10.766805
Sum16992
Variance78.438147
MonotonicityNot monotonic
2025-03-09T10:10:43.988810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 785
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
1 190
 
6.4%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
Other values (46) 332
11.2%
ValueCountFrequency (%)
1 190
 
6.4%
2 785
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

qtd_items
Real number (ℝ)

High correlation 

Distinct1671
Distinct (%)56.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1608.8525
Minimum1
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-09T10:10:44.205861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile102.4
Q1296
median641
Q31401
95-th percentile4407.4
Maximum196844
Range196843
Interquartile range (IQR)1105

Descriptive statistics

Standard deviation5887.578
Coefficient of variation (CV)3.6594891
Kurtosis465.99808
Mean1608.8525
Median Absolute Deviation (MAD)422
Skewness17.858591
Sum4776683
Variance34663575
MonotonicityNot monotonic
2025-03-09T10:10:44.445433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 11
 
0.4%
150 9
 
0.3%
88 9
 
0.3%
84 8
 
0.3%
260 8
 
0.3%
288 8
 
0.3%
272 8
 
0.3%
246 8
 
0.3%
114 7
 
0.2%
134 7
 
0.2%
Other values (1661) 2886
97.2%
ValueCountFrequency (%)
1 1
< 0.1%
2 2
0.1%
12 2
0.1%
16 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
23 1
< 0.1%
25 1
< 0.1%
ValueCountFrequency (%)
196844 1
< 0.1%
80997 1
< 0.1%
80263 1
< 0.1%
77373 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
63312 1
< 0.1%
58343 1
< 0.1%
57885 1
< 0.1%

qtd_products
Real number (ℝ)

High correlation 

Distinct468
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.72415
Minimum1
Maximum7838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-09T10:10:44.762699image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q129
median67
Q3135
95-th percentile382
Maximum7838
Range7837
Interquartile range (IQR)106

Descriptive statistics

Standard deviation269.89641
Coefficient of variation (CV)2.1992119
Kurtosis354.86113
Mean122.72415
Median Absolute Deviation (MAD)44
Skewness15.707635
Sum364368
Variance72844.071
MonotonicityNot monotonic
2025-03-09T10:10:45.009921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 43
 
1.4%
20 37
 
1.2%
29 35
 
1.2%
35 35
 
1.2%
19 34
 
1.1%
15 33
 
1.1%
11 32
 
1.1%
26 31
 
1.0%
27 30
 
1.0%
25 30
 
1.0%
Other values (458) 2629
88.5%
ValueCountFrequency (%)
1 6
 
0.2%
2 14
0.5%
3 16
0.5%
4 17
0.6%
5 26
0.9%
6 29
1.0%
7 18
0.6%
8 19
0.6%
9 26
0.9%
10 28
0.9%
ValueCountFrequency (%)
7838 1
< 0.1%
5673 1
< 0.1%
5095 1
< 0.1%
4580 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1637 1
< 0.1%

avg_ticket
Real number (ℝ)

High correlation  Skewed 

Distinct2000
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.897713
Minimum2.15
Maximum56157.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-09T10:10:45.233508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2.15
5-th percentile4.918
Q113.12
median17.96
Q324.99
95-th percentile90.498
Maximum56157.5
Range56155.35
Interquartile range (IQR)11.87

Descriptive statistics

Standard deviation1036.9344
Coefficient of variation (CV)19.980349
Kurtosis2890.7071
Mean51.897713
Median Absolute Deviation (MAD)5.98
Skewness53.444224
Sum154084.31
Variance1075233
MonotonicityNot monotonic
2025-03-09T10:10:45.450569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.49 7
 
0.2%
17.66 6
 
0.2%
16.39 6
 
0.2%
16.82 6
 
0.2%
16.92 6
 
0.2%
19.06 6
 
0.2%
20.75 5
 
0.2%
10 5
 
0.2%
18.38 5
 
0.2%
17.71 5
 
0.2%
Other values (1990) 2912
98.1%
ValueCountFrequency (%)
2.15 1
< 0.1%
2.43 1
< 0.1%
2.46 1
< 0.1%
2.51 1
< 0.1%
2.52 1
< 0.1%
2.65 1
< 0.1%
2.66 1
< 0.1%
2.71 1
< 0.1%
2.76 1
< 0.1%
2.77 1
< 0.1%
ValueCountFrequency (%)
56157.5 1
< 0.1%
4453.43 1
< 0.1%
3202.92 1
< 0.1%
1687.2 1
< 0.1%
952.99 1
< 0.1%
872.13 1
< 0.1%
841.02 1
< 0.1%
651.17 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%

avg_recency_days
Real number (ℝ)

High correlation 

Distinct1258
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-67.348511
Minimum-366
Maximum-1
Zeros0
Zeros (%)0.0%
Negative2969
Negative (%)100.0%
Memory size46.4 KiB
2025-03-09T10:10:45.668618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-366
5-th percentile-201
Q1-85.333333
median-48.285714
Q3-25.923077
95-th percentile-8
Maximum-1
Range365
Interquartile range (IQR)59.410256

Descriptive statistics

Standard deviation63.544929
Coefficient of variation (CV)-0.94352388
Kurtosis4.8871091
Mean-67.348511
Median Absolute Deviation (MAD)26.285714
Skewness-2.0627709
Sum-199957.73
Variance4037.958
MonotonicityNot monotonic
2025-03-09T10:10:45.912663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-14 25
 
0.8%
-4 22
 
0.7%
-70 21
 
0.7%
-7 20
 
0.7%
-35 19
 
0.6%
-49 18
 
0.6%
-21 17
 
0.6%
-46 17
 
0.6%
-11 17
 
0.6%
-42 16
 
0.5%
Other values (1248) 2777
93.5%
ValueCountFrequency (%)
-366 1
 
< 0.1%
-365 1
 
< 0.1%
-363 1
 
< 0.1%
-362 1
 
< 0.1%
-357 2
0.1%
-356 1
 
< 0.1%
-355 2
0.1%
-352 1
 
< 0.1%
-351 2
0.1%
-350 3
0.1%
ValueCountFrequency (%)
-1 16
0.5%
-1.5 1
 
< 0.1%
-2 13
0.4%
-2.5 1
 
< 0.1%
-2.601398601 1
 
< 0.1%
-3 15
0.5%
-3.321428571 1
 
< 0.1%
-3.330357143 1
 
< 0.1%
-3.5 2
 
0.1%
-4 22
0.7%

frequency
Real number (ℝ)

High correlation  Skewed 

Distinct1225
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1137973
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-09T10:10:46.520802image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0088941642
Q10.016339869
median0.025889968
Q30.049450549
95-th percentile1
Maximum17
Range16.99455
Interquartile range (IQR)0.03311068

Descriptive statistics

Standard deviation0.40815625
Coefficient of variation (CV)3.5866953
Kurtosis989.36508
Mean0.1137973
Median Absolute Deviation (MAD)0.012191338
Skewness24.880491
Sum337.8642
Variance0.16659153
MonotonicityNot monotonic
2025-03-09T10:10:46.739861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 198
 
6.7%
0.0625 18
 
0.6%
0.02777777778 17
 
0.6%
0.02380952381 16
 
0.5%
0.08333333333 15
 
0.5%
0.09090909091 15
 
0.5%
0.02941176471 14
 
0.5%
0.03448275862 14
 
0.5%
0.02564102564 13
 
0.4%
0.01923076923 13
 
0.4%
Other values (1215) 2636
88.8%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
3 1
 
< 0.1%
2 6
 
0.2%
1.142857143 1
 
< 0.1%
1 198
6.7%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5335120643 1
 
< 0.1%
0.5 3
 
0.1%

qtd_returns
Real number (ℝ)

Skewed  Zeros 

Distinct214
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.156955
Minimum0
Maximum80995
Zeros1481
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-09T10:10:46.963901image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q39
95-th percentile100.6
Maximum80995
Range80995
Interquartile range (IQR)9

Descriptive statistics

Standard deviation1512.4961
Coefficient of variation (CV)24.333498
Kurtosis2765.5286
Mean62.156955
Median Absolute Deviation (MAD)1
Skewness51.797744
Sum184544
Variance2287644.6
MonotonicityNot monotonic
2025-03-09T10:10:47.210959image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
49.9%
1 164
 
5.5%
2 148
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
6 78
 
2.6%
5 61
 
2.1%
12 51
 
1.7%
8 43
 
1.4%
7 43
 
1.4%
Other values (204) 706
23.8%
ValueCountFrequency (%)
0 1481
49.9%
1 164
 
5.5%
2 148
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
5 61
 
2.1%
6 78
 
2.6%
7 43
 
1.4%
8 43
 
1.4%
9 41
 
1.4%
ValueCountFrequency (%)
80995 1
< 0.1%
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%

avg_basket_size
Real number (ℝ)

High correlation  Skewed 

Distinct1979
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.81376
Minimum1
Maximum40498.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-09T10:10:47.443374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44
Q1103.25
median172.33333
Q3281.69231
95-th percentile600
Maximum40498.5
Range40497.5
Interquartile range (IQR)178.44231

Descriptive statistics

Standard deviation791.55519
Coefficient of variation (CV)3.1685812
Kurtosis2255.5382
Mean249.81376
Median Absolute Deviation (MAD)83.083333
Skewness44.672717
Sum741697.07
Variance626559.62
MonotonicityNot monotonic
2025-03-09T10:10:47.685437image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
114 10
 
0.3%
73 9
 
0.3%
86 9
 
0.3%
82 9
 
0.3%
136 8
 
0.3%
75 8
 
0.3%
88 8
 
0.3%
60 8
 
0.3%
130 7
 
0.2%
Other values (1969) 2882
97.1%
ValueCountFrequency (%)
1 2
0.1%
2 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
40498.5 1
< 0.1%
6009.333333 1
< 0.1%
4282 1
< 0.1%
3906 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2801 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%

avg_unique_basket_size
Real number (ℝ)

High correlation 

Distinct1005
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.154708
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-09T10:10:47.908479image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.3454545
Q110
median17.2
Q327.75
95-th percentile56.94
Maximum299.70588
Range298.70588
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation19.512322
Coefficient of variation (CV)0.88073027
Kurtosis27.703297
Mean22.154708
Median Absolute Deviation (MAD)8.2
Skewness3.4994559
Sum65777.329
Variance380.73071
MonotonicityNot monotonic
2025-03-09T10:10:48.132531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 53
 
1.8%
14 39
 
1.3%
11 38
 
1.3%
9 33
 
1.1%
20 33
 
1.1%
1 32
 
1.1%
17 31
 
1.0%
18 30
 
1.0%
10 30
 
1.0%
16 29
 
1.0%
Other values (995) 2621
88.3%
ValueCountFrequency (%)
1 32
1.1%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
0.1%
1.5 8
 
0.3%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 24
0.8%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
259 1
< 0.1%
203.5 1
< 0.1%
148 1
< 0.1%
145 1
< 0.1%
136.125 1
< 0.1%
135.5 1
< 0.1%
127 1
< 0.1%
122 1
< 0.1%
118 1
< 0.1%

Interactions

2025-03-09T10:10:39.401832image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:13.220897image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:15.771725image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:18.380816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:20.816431image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:23.277186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:25.532698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:27.698189image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:30.071726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:32.235216image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:34.428780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:37.211510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:39.573863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:13.406941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:15.952264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:18.565858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:20.995669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:23.472228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:25.705739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:27.855224image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:30.250777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:32.403257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:34.606820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:37.388548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:39.740156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:13.585981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:16.122301image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:18.757900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:21.188713image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:23.649270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:25.880779image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:28.013259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:30.422807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:32.575294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:34.790862image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:37.561589image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:39.911194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:13.767022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:16.313349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:18.940942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:21.362752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:23.837312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:26.059817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:28.536381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:30.597847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:32.751334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:35.003911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:37.743639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:40.078233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:13.956066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:16.518392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:19.116985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:21.748841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:24.015352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:26.228855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:28.693416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:30.768885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:32.915374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:35.275073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:37.916487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:40.259273image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:14.237128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:16.867471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:19.340032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:21.942883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:24.204395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:26.418907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:28.877457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:30.958928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:33.117419image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:35.579137image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:38.110528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:40.437314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:14.458179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:17.082520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:19.554081image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:22.137932image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:24.396450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:26.594938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:29.060496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:31.146973image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:33.299462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:35.784187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:38.295572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:40.609354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-03-09T10:10:17.262562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:19.748125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:22.310966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:24.582483image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:26.770978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:29.212530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:31.322010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:33.472509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:35.960229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:38.467611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:40.785390image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:14.826270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:17.458606image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:19.949236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:22.491013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:24.774536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:26.955024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:29.380569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:31.505052image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:33.651537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:36.143268image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:38.653654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:41.016447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:15.010312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:17.689659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:20.185288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:22.683051image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:24.965569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:27.138061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:29.552608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:31.682094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:33.823579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:36.329317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:38.833694image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:41.214490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:15.216359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:17.931714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:20.401336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:22.892099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:25.159612image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:27.334107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:29.732651image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:31.873137image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:34.005619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:36.511352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:39.025736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:41.401534image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:15.595459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:18.130758image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:20.619386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:23.108148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:25.350657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:27.522151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:29.905689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:32.061177image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:34.248675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:37.018476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-09T10:10:39.217779image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-09T10:10:48.304569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketavg_unique_basket_sizecustomer_idfrequencygross_revenueqtd_invoicesqtd_itemsqtd_productsqtd_returnsrecency_days
avg_basket_size1.0000.0770.1880.447-0.1230.0270.5740.1000.7290.3830.210-0.098
avg_recency_days0.0771.0000.122-0.048-0.0190.8810.2470.2590.2270.1660.396-0.108
avg_ticket0.1880.1221.000-0.611-0.1310.0910.2460.0590.167-0.3770.1900.048
avg_unique_basket_size0.447-0.048-0.6111.000-0.007-0.0720.2910.0250.3200.6990.019-0.106
customer_id-0.123-0.019-0.131-0.0071.000-0.002-0.0760.026-0.0700.013-0.0630.001
frequency0.0270.8810.091-0.072-0.0021.0000.0900.0790.0800.0360.2340.018
gross_revenue0.5740.2470.2460.291-0.0760.0901.0000.7700.9250.7440.372-0.415
qtd_invoices0.1000.2590.0590.0250.0260.0790.7701.0000.7160.6900.294-0.502
qtd_items0.7290.2270.1670.320-0.0700.0800.9250.7161.0000.7300.344-0.408
qtd_products0.3830.166-0.3770.6990.0130.0360.7440.6900.7301.0000.242-0.435
qtd_returns0.2100.3960.1900.019-0.0630.2340.3720.2940.3440.2421.000-0.120
recency_days-0.098-0.1080.048-0.1060.0010.018-0.415-0.502-0.408-0.435-0.1201.000

Missing values

2025-03-09T10:10:41.659591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-09T10:10:41.881640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_daysqtd_invoicesqtd_itemsqtd_productsavg_ticketavg_recency_daysfrequencyqtd_returnsavg_basket_sizeavg_unique_basket_size
0178505391.21372.034.01733.0297.018.15-35.50000017.00000040.050.9705888.735294
1130473232.5956.09.01390.0171.018.90-27.2500000.02830235.0154.44444419.000000
2125836705.382.015.05028.0232.028.90-23.1875000.04032350.0335.20000015.466667
313748948.2595.05.0439.028.033.87-92.6666670.0179210.087.8000005.600000
415100876.00333.03.080.03.0292.00-8.6000000.07317122.026.6666671.000000
5152914623.3025.014.02102.0102.045.33-23.2000000.04011529.0150.1428577.285714
6146885630.877.021.03621.0327.017.22-18.3000000.057221399.0172.42857115.571429
7178095411.9116.012.02057.061.088.72-35.7000000.03352041.0171.4166675.083333
81531160767.900.091.038194.02379.025.54-4.1444440.243316474.0419.71428626.142857
9160982005.6387.07.0613.067.029.93-47.6666670.0243900.087.5714299.571429
customer_idgross_revenuerecency_daysqtd_invoicesqtd_itemsqtd_productsavg_ticketavg_recency_daysfrequencyqtd_returnsavg_basket_sizeavg_unique_basket_size
5627177271060.2515.01.0645.066.016.06-6.01.0000006.0645.00000066.0
563717232421.522.02.0203.036.011.71-12.00.1538460.0101.50000018.0
563817468137.0010.02.0116.05.027.40-4.00.4000000.058.0000002.5
564913596697.045.02.0406.0166.04.20-7.00.2500000.0203.00000083.0
5655148931237.859.02.0799.073.016.96-2.00.6666670.0399.50000036.5
565912479473.2011.01.0382.030.015.77-4.01.00000034.0382.00000030.0
568014126706.137.03.0508.015.047.08-3.00.75000050.0169.3333335.0
5686135211092.391.03.0733.0435.02.51-4.50.3000000.0244.333333145.0
569615060301.848.04.0262.0120.02.52-1.02.0000000.065.50000030.0
571512558269.967.01.0196.011.024.54-6.01.000000196.0196.00000011.0